code: def convert_to_cudf(cp_arrays):
      (
          cp_src,
          cp_dst,
          cp_edge_weights,
          cp_edge_ids,
          cp_edge_types,
      ) = cp_arrays
  
      df = cudf.DataFrame()
      df["src"] = cp_src
      df["dst"] = cp_dst
  
      if cp_edge_weights is not None:
          df["weights"] = cp_edge_weights
      if cp_edge_ids is not None:
          df["edge_id"] = cp_edge_ids
      if cp_edge_types is not None:
          df["edge_type"] = cp_edge_types
  
      return df
  
file_path: cugraph/python/cugraph/cugraph/generators/rmat.py
imports: from dask.distributed import default_client, wait
  import dask_cudf
  from cugraph.dask.comms import comms
  import cudf
  import numpy
  import cupy
  import cugraph
  from pylibcugraph import generate_rmat_edgelist
  from pylibcugraph import generate_rmat_edgelists
  from pylibcugraph import ResourceHandle
label_desc: Use image node_id 3 for calling a global function with example usage: convert_to_cudf(cp_arrays) and returns: df